Dr. Milana Frenkel-Morgenstern

Dr. Milana Frenkel-Morgenstern research interest is in strategy to identify unique potential drug targets in cancer cells.

http://medweb.md.biu.ac.il/research/milana-morgenstern

ABOUT MY WORK

The drug targets we are looking for are abnormal fusion transcripts, also known as “chimeric RNAs,” that can be shown to exist only, or predominantly, in various cancer cells. Dr. Frenkel-Morgenstern catalogues these cancer-associated fusion transcripts, then she analyses the function of the proteins produced by the transcripts in order to find potential drug targets. The key challenge is to identify those fusion events that are directly related to biochemical cell function

SELECTED PUBLICATIONS

1) Tagore S, Gorohovski A, Jensen LJ, Frenkel-Morgenstern M (2019) ProtFus: A Comprehensive Method Characterizing Protein-Protein Interactions of Fusion Proteins. PLoS Comput Biol 15(8): e1007239. https://doi.org/10.1371/journal.pcbi.1007239

2) Frenkel-Morgenstern M, Voet H, Pietrokovski S. Enhanced statistics for local alignment of multiple alignments improves prediction of protein function and structure. Bioinformatics, 2005; 21(13):2950-6. PMID: 15870168. [Impact Factor:5.3, rank: 1/43 in Bioinformatics and Computational Biology, cited by 11 papers]

3) Frenkel-Morgenstern M, Singer A, Bronfeld H, Pietrokovski S. One-Block CYRCA: an automated procedure for identifying multiple-block alignments from single block queries. Nucleic Acids Res., 2005, 33: W281-3. PMID: 15980470. [Impact Factor: 8.3, rank: 10% top, 27/290 in Biochemistry & Molecular Biology, cited by 3 papers]

4) Eyal E*, Frenkel-Morgenstern M*, Sobolev V, Pietrokovski S. A pair-to-pair amino acids substitution matrix and its applications for protein structure prediction.Proteins: Structure, Function, and Bioinformatics, 2007, 67(1):142-53. PMID: 17243158. [Impact Factor: 3.4, Ranking: 2012: 25/72 in Biophysics; 108/290 in Biochemistry & Molecular Biology, cited by 21 papers]

5) Frenkel-Morgenstern M, Magid R, Eyal E, Pietrokovski S. Refining intra-protein contact prediction by graph analysis. BMC Bioinformatics, 2007, 8 Suppl 5:S6. PMID: 17570865. [Impact Factor: 3.2 rank: 3/43 of all the Bioinformatics and Computational Biology journals, cited by 5 papers]

6) Klipcan L, Frenkel-Morgenstern M, Safro MG. Presence of tRNA-dependent pathways correlates with high cysteine content in methanogenic Archaea. Trends in Genetics. 2008. 24(2):59-63, PMID: 18192060. [Impact Factor: 10.1, rank: 5% top, 10/170 in Genetics and Heredity, cited by 12 papers]

7)  Calabrese, C., Davidson, N.R., Demircioğlu, D. et al. Genomic basis for RNA alterations in cancerNature 578, 129–136 (2020)

8) Campbell, P.J., Getz, G., Korbel, J.O. et al. Pan-cancer analysis of whole genomesNature 578, 82–93 (2020). https://doi.org/10.1038/s41586-020-1969-6

RESEARCH PROJECTS

• Study alterations in the metabolic networks of fusion proteins for understanding the onco-fusions which are drivers in cancer development and progression.
• The literature text-mining approach to identify cancer fusion proteins and networks in order to classify the network alterations in cancers